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Fast segmentation of 3D data using an octree
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Orientador(es)
Resumo(s)
The algorithm developed uses an octree pyramid
in which noise is reduced at the expense of the spatial
resolution. At a certain level an unsupervised clustering
without spatial connectivity constraints is applied.
After the classification, isolated voxels and insignificant
regions are removed by assigning them to their neighbours.
The spatial resolution is then increased by the
downprojection of the regions, level by level. At each
level the uncertainty of the boundary voxels is minimised
by a dynamic selection and classification of these, using
an adaptive 3D filtering. The algorithm is tested using
different data sets, including NMR data.
Descrição
Palavras-chave
Segmentação de imagem em 3D 3D segmentation Boundary refinement Octree NMR data
Contexto Educativo
Citação
11th Portuguese Conference on Pattern Recognition (RECPAD 2000). - Porto, 11-12 May 2000. - p. 185-189
Editora
Porto